Earlier quoted context omitted.
Yeah, me too actually. Especially when searching for things like PC parts, Newegg does way better (though PC Part Picker is even better). I feel bad not buying from the interface that worked best... but Newegg's order process is pretty evil, so I don't feel that bad. ("Pay $9 to have your order shipped possibly today, instead of waiting an unspecified amount of time." Do they still do that? I saw that once and never…
I call this the "massive heterogeneous catalog" problem. Generally e-commerce retailers have grown from a fairly narrow set of product categories (e.g. books for Amazon) to adding more and more diverse categories. This has a dramatic impact on site search quality. If you consider a simple example, shoes. You only need a couple of facets to filter products to a reasonable set to browse through: gender and size. Now st…
Systems like Solr, elastic search and endeca (out of the box) all assume relevance means keyword frequency in a product page, with some weighting depending of title, description, tag, etc. Delivering relevant results that users might want to purchase requires taking these systems, adding or customizing their NLP techniques, operationalizing historical user search & purchase data to determine intent, personalizing by shopper history, etc.
The challenges of massive heterogenous catalog affect other areas... Chief among them search result personalization… an individual’s gaming purchase history might cause ‘button down’ to return gaming keyboards, rather than oxford shirts, while a pet products purchase history could lead to a search for turkey returning turkey dog food.
The fact that Amazon fails to personalize search results is evidence of the difficulty & opportunity here. The sort of pervasive personalization found in AirBnb, facebook, google are simply out of reach of most ecommerce retailers…